test_that("t-stat equivalence OLS - R and R-lean", { lm_fit <- lm( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ) ) B <- 999 # adj= FALSE # cluster.adj= FALSE # cluster.df= "conventional" # impose_null= TRUE # engine = "R" for (engine in c("R")) { for (adj in c(TRUE, FALSE)) { for (cluster.adj in c(TRUE, FALSE)) { for (cluster.df in c("conventional", "min")) { for (impose_null in c(TRUE, FALSE)) { # oneway clustering feols_fit <- fixest::feols( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ), cluster = ~group_id1, ssc = fixest::ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ) ) dof_tstat <- fixest::tstat(feols_fit)[c( "treatment", "log_income", "ideology1" )] boot1 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "treatment", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot2 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "log_income", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot3 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "ideology1", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) expect_equal(abs(teststat(boot1)), abs(dof_tstat[1]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot2)), abs(dof_tstat[2]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot3)), abs(dof_tstat[3]), ignore_attr = TRUE ) if (engine != "R-lean") { } # twoway clustering feols_fit <- fixest::feols( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ), cluster = ~ group_id1 + group_id2, ssc =fixest::ssc( adj = adj, # fixef.K = "full", cluster.adj = cluster.adj, cluster.df = cluster.df ) ) dof_tstat <- fixest::coeftable(feols_fit)[c( "treatment", "log_income", "ideology1" ), 3] boot1 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1", "group_id2"), B = B, param = "treatment", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot2 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1", "group_id2"), B = B, param = "log_income", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot3 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1", "group_id2"), B = B, param = "ideology1", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) expect_equal(abs(teststat(boot1)), abs(dof_tstat[1]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot2)), abs(dof_tstat[2]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot3)), abs(dof_tstat[3]), ignore_attr = TRUE ) } } } } } for (engine in c("R-lean")) { for (adj in c(TRUE, FALSE)) { for (cluster.adj in c(TRUE, FALSE)) { for (cluster.df in c("conventional", "min")) { for (impose_null in c(TRUE)) { # oneway clustering feols_fit <- fixest::feols( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ), cluster = ~group_id1, ssc =fixest::ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ) ) dof_tstat <- fixest::tstat(feols_fit)[c( "treatment", "log_income", "ideology1" )] boot1 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "treatment", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot2 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "log_income", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot3 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "ideology1", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) expect_equal(abs(teststat(boot1)), abs(dof_tstat[1]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot2)), abs(dof_tstat[2]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot3)), abs(dof_tstat[3]), ignore_attr = TRUE ) } } } } } }) test_that("t-stat equivalence OLS - WildBootTests", { skip_on_cran() skip_if_not( fwildclusterboot:::find_proglang("julia"), message = "skip test as julia installation not found." ) lm_fit <- lm( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ) ) B <- 999 for (engine in c("WildBootTests.jl")) { for (adj in c(TRUE, FALSE)) { for (cluster.adj in c(TRUE, FALSE)) { for (cluster.df in c("conventional", "min")) { for (impose_null in c(TRUE, FALSE)) { # oneway clustering feols_fit <- fixest::feols( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ), cluster = ~group_id1, ssc = fixest::ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ) ) dof_tstat <- fixest::tstat(feols_fit)[c( "treatment", "log_income", "ideology1" )] boot1 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "treatment", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot2 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "log_income", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot3 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1"), B = B, param = "ideology1", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) expect_equal(abs(boot1$t_stat), abs(dof_tstat[1]), ignore_attr = TRUE ) expect_equal(abs(boot2$t_stat), abs(dof_tstat[2]), ignore_attr = TRUE ) expect_equal(abs(boot3$t_stat), abs(dof_tstat[3]), ignore_attr = TRUE ) # twoway clustering feols_fit <- fixest::feols( proposition_vote ~ treatment + ideology1 + log_income, data = fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.81, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 970691 ), cluster = ~ group_id1 + group_id2, ssc =fixest::ssc( adj = adj, # fixef.K = "full", cluster.adj = cluster.adj, cluster.df = cluster.df ) ) dof_tstat <- fixest::coeftable(feols_fit)[c( "treatment", "log_income", "ideology1" ), 3] boot1 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1", "group_id2"), B = B, param = "treatment", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot2 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1", "group_id2"), B = B, param = "log_income", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) boot3 <- suppressWarnings( fwildclusterboot::boottest( lm_fit, clustid = c("group_id1", "group_id2"), B = B, param = "ideology1", ssc = boot_ssc( adj = adj, cluster.adj = cluster.adj, cluster.df = cluster.df ), impose_null = impose_null, engine = engine ) ) expect_equal(abs(teststat(boot1)), abs(dof_tstat[1]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot2)), abs(dof_tstat[2]), ignore_attr = TRUE ) expect_equal(abs(teststat(boot3)), abs(dof_tstat[3]), ignore_attr = TRUE ) } } } } } }) # exact tests test_that("t-stat equivalence OLS q > 1", { skip_on_cran() skip_if_not( fwildclusterboot:::find_proglang("julia"), message = "skip test as julia installation not found." ) wald_test <- function(run_this_test) { if (run_this_test) { reltol <- 0.002 N <- 1000 data1 <<- fwildclusterboot:::create_data( N = 1000, N_G1 = 20, icc1 = 0.5, N_G2 = 20, icc2 = 0.2, numb_fe1 = 10, numb_fe2 = 10, seed = 90864369, weights = 1:N / N ) feols_fit <- fixest::feols(proposition_vote ~ treatment + log_income + year, data = data1 ) lm_fit <- lm(proposition_vote ~ treatment + log_income + year, data = data1 ) feols_fit_weights <- fixest::feols( proposition_vote ~ treatment + log_income + year, data = data1, weights = data1$weights ) lm_fit_weights <- lm( proposition_vote ~ treatment + log_income + year, data = data1, weights = data1$weights ) N <- nrow(data1) k <- length(coef(lm_fit)) G <- length(unique(data1$group_id1)) type <- "rademacher" p_val_type <- "two-tailed" # impose_null <- TRUE # OLS # 1) oneway clustering # one hypothesis R <- clubSandwich::constrain_zero(constraints = 2, coefs = coef(lm_fit)) boot_jl <- suppressWarnings(mboottest( lm_fit, R = R, clustid = "group_id1", B = 999 )) # sW <- coeftest(object, vcov = sandwich::vcovCL(object, # cluster = ~ group_id1)) wald_stat <- fixest::wald(feols_fit, "treatment", cluster = ~group_id1) expect_equal(boot_jl$teststat, sqrt(wald_stat$stat), ignore_attr = TRUE) # two hypotheses R <- clubSandwich::constrain_zero(constraints = 1:2, coefs = coef(lm_fit)) boot_jl <- suppressWarnings(suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", object = lm_fit, R = R, clustid = "group_id1", B = 999, ssc = fwildclusterboot::boot_ssc( adj = TRUE, cluster.adj = TRUE ) ) )) wald_stat <- fixest::wald(feols_fit, "Inter|treatment", cluster = ~group_id1) expect_equal(boot_jl$teststat, wald_stat$stat, ignore_attr = TRUE) # one hypothesis R <- clubSandwich::constrain_zero(constraints = 2, coefs = coef(lm_fit)) boot_jl <- suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", lm_fit, R = R, clustid = c("group_id1", "group_id2"), B = 999, ssc = boot_ssc(cluster.df = "min") ) ) # sW <- coeftest(object, vcov = sandwich::vcovCL(object, # cluster = ~ group_id1)) wald_stat <- fixest::wald( feols_fit, "treatment", cluster = ~ group_id1 + group_id2, ssc =fixest::ssc(cluster.df = "min") ) expect_equal(teststat(boot_jl), sqrt(wald_stat$stat), ignore_attr = TRUE) # two hypotheses R <- clubSandwich::constrain_zero(constraints = 1:2, coefs = coef(lm_fit)) boot_jl <- suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", object = lm_fit, R = R, clustid = "group_id1", B = 999, ssc = fwildclusterboot::boot_ssc( adj = TRUE, cluster.adj = TRUE ) ) ) wald_stat <- fixest::wald( feols_fit, "Inter|treatment", cluster = ~group_id1, cluster.df = "conventional" ) expect_equal(teststat(boot_jl), wald_stat$stat, ignore_attr = TRUE) # WLS # 1) oneway clustering # one hypothesis R <- clubSandwich::constrain_zero( constraints = 2, coefs = coef(lm_fit_weights) ) boot_jl <- suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", lm_fit_weights, R = R, clustid = "group_id1", B = 999 ) ) wald_stat <- fixest::wald(feols_fit_weights, "treatment", cluster = ~group_id1) expect_equal(teststat(boot_jl), sqrt(wald_stat$stat), ignore_attr = TRUE) # two hypotheses R <- clubSandwich::constrain_zero( constraints = 1:2, coefs = coef(lm_fit_weights) ) boot_jl <- suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", object = lm_fit_weights, R = R, clustid = "group_id1", B = 999, ssc = fwildclusterboot::boot_ssc( adj = TRUE, cluster.adj = TRUE ) ) ) wald_stat <- fixest::wald(feols_fit_weights, "Inter|treatment", cluster = ~group_id1 ) expect_equal(teststat(boot_jl), wald_stat$stat, ignore_attr = TRUE) # one hypothesis R <- clubSandwich::constrain_zero( constraints = 2, coefs = coef(lm_fit_weights) ) boot_jl <- suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", lm_fit_weights, R = R, clustid = c("group_id1", "group_id2"), B = 999, type = type, p_val_type = p_val_type, ssc = boot_ssc(cluster.df = "min") ) ) wald_stat <- fixest::wald( feols_fit_weights, "treatment", cluster = ~ group_id1 + group_id2, ssc =fixest::ssc(cluster.df = "min") ) expect_equal(teststat(boot_jl), sqrt(wald_stat$stat), ignore_attr = TRUE) # two hypotheses R <- clubSandwich::constrain_zero( constraints = 1:2, coefs = coef(lm_fit_weights) ) boot_jl <- suppressWarnings( fwildclusterboot::mboottest( floattype = "Float64", object = lm_fit_weights, R = R, clustid = "group_id1", B = 999, ssc = boot_ssc(cluster.adj = TRUE) ) ) wald_stat <- fixest::wald( feols_fit_weights, "Inter|treatment", cluster = ~group_id1, cluster.df = "conventional" ) expect_equal(teststat(boot_jl), wald_stat$stat, ignore_attr = TRUE) } } wald_test(run_this_test = TRUE) }) test_that("t-stat equivalence IV", { skip_on_cran() skip_if_not( fwildclusterboot:::find_proglang("julia"), message = "skip test as julia installation not found." ) iv_test <- function(run_this_test) { # Note: Test with Float64 for exact match if (run_this_test) { set.seed(123) data("SchoolingReturns", package = "ivreg") # drop all NA values from SchoolingReturns data1 <<- na.omit(SchoolingReturns) ivreg_fit <- ivreg::ivreg( log(wage) ~ education + age + ethnicity + smsa + south + parents14 | nearcollege + age + ethnicity + smsa + south + parents14, data = data1 ) vcov1 <- sandwich::vcovCL( ivreg_fit, cluster = ~kww, cadjust = TRUE, type = "HC1" ) vcov2 <- sandwich::vcovCL( ivreg_fit, cluster = ~ smsa + kww, cadjust = TRUE, type = "HC1" ) res1 <- lmtest::coeftest(ivreg_fit, vcov1) res_df1 <- as.data.frame(broom::tidy(res1)) res2 <- lmtest::coeftest(ivreg_fit, vcov2) res_df2 <- as.data.frame(broom::tidy(res2)) boot_ivreg1 <- suppressWarnings( boottest( floattype = "Float64", object = ivreg_fit, B = 999, param = "education", clustid = "kww", type = "mammen", impose_null = TRUE ) ) expect_equal(teststat(boot_ivreg1), as.vector(res_df1[res_df1$term == "education", "statistic"]), ignore_attr = TRUE ) boot_ivreg2 <- boottest( floattype = "Float64", object = ivreg_fit, B = 999, param = "education", clustid = c("smsa", "kww"), type = "rademacher" ) expect_equal(teststat(boot_ivreg2), res_df2[ res_df2$term == "education", "statistic" ]) } } iv_test(run_this_test = TRUE) })